Methodology Of Business Ecosystems Network
Analysis: A Field Study In Telecom Italia
Future Centre
Cinzia Battistella, Katia Colucci, and Fabio Nonino
Abstract The scope of this paper is the analysis of the business ecosystems, as
reticular structures interacting one with each other. The aim is to propose a methodology for analyzing and modeling the ecosystems and to illustrate its application via a field study conducted inside the Telecom Italia Future Centre, and in
particular the digital imaging ecosystem. The methodology is called methodology
of business ecosystem network analysis (MOBENA).
1. Introduction
Today’s dynamic and complex environment requires a higher level, network view
of inter-organizational exchanges at both the conceptual and practical level. The
Value Chain and the Value Network models (Porter, 1985; Allee, 2002) are concepts focused on the value creation process of the firm, instead the Business Ecosystem (Moore, 1993; Iansiti and Levien, 2004) concept is useful to understand
complex inter-firms relationships which form the background of the value creation
process. In fact, the success of a business ecosystem lies in the combination of efforts from business, government, education, and all segments of the community.
The cultural and two-sided interactions between actors of a community sharing the
same values and especially the same interests have the implicit objective of longterm sustainability of the whole community. While value chains are based on
volatile supplier/buyer relationships, the business ecosystems are based on a network of multi-directional relationships with firms with shared values and interests.
The relationships are both monetary and not monetary, and the winners are those
actors who can leverage network externalities. Whereas value chains are essentially defined by the accumulated value generated by monetary relationships, business
ecosystems are also defined by the non-monetary advantages derived by firms participating in them. Therefore, a business ecosystems growth depends also on the
quality of the non-monetary, qualitative interactions between stakeholders. These
interactions create something intangible that is shared by all participants, the social capital (see Durlauf and Fafchamps, 2004; De Toni and Nonino, 2010). Networks, common norms, shared values and trust, comparable expectations, brought
forth in cooperation and business relationships, create a web of social relations
that have productive benefits by facilitating coordinated actions. While value
2
chains create value, business ecosystems generate value and social capital, resulting in a long-term and sustainable relationships.
If a company would like to know the complex dynamics intercepting it and/or
if it would like to enter and act in an ecosystem, it has to rely on a deep knowledge
and analysis of the ecosystem itself. It is a matter of identifying and describing the
ecosystem components, the relationships between them and the balance of power
that guarantees their existence. All these elements together define the shape and
behaviour pattern: how the ecosystem “lives”. Moreover, also the time variable is
fundamental: the relationships between the constituent elements may change the
ecosystem structure. So, understanding the ecosystem means not only drawing the
shape and relationships among the constituent elements in a certain moment in
time, but understanding how it can evolve by monitoring the evolutionary trends
with all the variables involved. It is thus important that companies establish monitoring processes for their ecosystem from a static and dynamic point of view, and
that they analyse business ecosystems and investigate how it can potentially impact their businesses. Clearly, these analyzes need to be supported by appropriate
tools and methodologies to work on. But, despite the importance of the practical
application of the business ecosystem concept as a representation of the real situation, literature on methodologies for business ecosystems is still in its infancy,
while the majority of the contributions are focused on the discussion of business
ecosystems per se (i.e. comparisons between natural ecosystems and business ecosystems, differences between value chain and business ecosystem, business ecosystems properties, their strategies, etc.). The scope of this paper is the analysis of
the business ecosystems, as reticular structures interacting one with each other.
The aim is to propose a methodology for analyzing and modeling the ecosystems
and to illustrate its application in a field study conducted inside the Telecom Italia
Future Centre. The methodology is called methodology of business ecosystem
network analysis (MOBENA).
The paper, after a discussion of the current literature on business ecosystems
(section 2), presents the field study methodological strategy (section 3) and introduces the MOBENA and its application in a peculiar business ecosystem in Telecom Italia, the digital photography ecosystem (section 4). Finally, it discusses the
findings and draws conclusions (section 5).
2. Modeling approaches of networks and ecosystems
Various approaches have been proposed to create a modeling language for firm interactions. In the view of Value Network, different modelling approaches have
been proposed, as the e3-value model (Gordijn et al., 2000), the c3-value
(Weigand et al., 2007) and the value network’s model of intangibles (Allee, 2002).
In the view of business ecosystems analysis, we found some first works all based
on agent-based modeling, such as the Business Ecosystem Analysis Methodology
(BEAM - Tian et al., 2009).
3
The following table (Table 1) shows a synthetic description of such methodologies, their main characteristics and compares them to our methodology. The
methodologies for business ecosystems are very few. The main problems that we
highlighted are that these methodologies are strongly interconnected to an agentbased modeling, therefore they over-simplify the problem. Moreover, they limit
potential for strategic analysis.
Table 1. Modeling approaches of value networks and business ecosystems
Model or methodology
Critiques
Investigated object
e3-value modeling (Gordijn et al., 2000)
Value network (theoretical basis: industrial
view)
c3-value model (Weigand et al., 2007)
Value network (theoretical basis: resourcebased view)
Value network model of intangibles (Alee,
2002)
Value network
Based on agent modeling; Lack of a clear strategic focus in the
model weakens its ability for prescriptive strategic insights
Based on agent modeling; It focuses on the direct competitor and
the direct customer; It neglects the inter-dependencies and the potential given by the network perspective
Analysis is mostly visual; It assumes that value is created through
exchanges; It is focused on intangibles exchanges; It does not assign a purpose to the network; It assumes that the network is not
manageable; It limits potential for strategic analysis
Agent based methodology (Marin et al., 2007)
Business ecosystem
Based on agent modeling; Focused only on tangible exchanges.
BEAM: business ecosystem analysis and
modeling (Tian et al., 2009)
Business ecosystem
Based on agent modeling; Lacks of a strategic focus
3. Research strategy
The present work is meant to help widen the knowledge basis on management of
ecosystems and proposes a methodology based on network analysis and foresight.
This paper attempts to answer to the following research questions: How is it possible to systematically study the structure and fluxes of a business ecosystem?
Increasingly, the technological innovations headed by ICT and TLC go beyond
the value chain where they have been originated to attract the interest of other value chains which are so far remote, with different actors, interests and market objectives. Therefore actors interact now in a business ecosystem. In this new context, previous business models can change and latent or even not existing markets
(and consequent business models) can emerge. That is why we decided to focus
our research on the TLC industry. Moreover, we took an exemplar case: the most
important TLC company in Italy, Telecom Italia (and in particular its unit focused
on economical studies and investigation of the future, the Telecom Italia Future
Centre). Among the ecosystems studied by the Future Centre, we chose to focus
on the digital imaging ecosystem. The research methodology includes an analysis
of literature on Strategic Management, Network Analysis and Foresight, from
whence the theoretical proposal of the methodology of business ecosystem network
4
analysis (MOBENA) was born. The case study design is opportune for presenting
a relevant overview of the importance and applicability of the methodology (Eisenhardt, 1989; McCutcheon and Meredith, 1993; Meredith, 1998). The object of
the case study is the test of the proposed methodology of business ecosystem network analysis. As described by Yin (2003), the case study research design can be
used to describe an intervention and its context. Some authors refer to this as a
“field experiment”. In the test in this study, the intervention is the application of
the proposed methodology, and the context is the company studied and in particular one of its ecosystems (the digital image ecosystem).
4. A proposal of a methodology for business ecosystems analysis
The methodology aims to provide a theoretical and operational framework for
analyzing the business ecosystems. It is designed to support the identification and
understanding of the business ecosystems by providing the criteria to define its
structure and analyze and evaluate the relevant behaviour. The methodology is
based on five steps. Table 2. MOBENA phases
PHASE and OBJECTIVES
CONTENT
DELIVERABLE
ECOSYSTEM PERIMETER,
ELEMENTS AND
RELATIONSHIPS
 Define the meaning of the ecosystem, decide what identifies it
and identify what defines its
boundaries.
 Detail the information to be collected as regards the constitutive elements and their relationships.
 Identify the seed – the actors’ attractor and the leverage for business.
 Identify the elements and their connections. Elements: players, technologies, products/services and
environment (market, constraints and regulation
forces)
Players: (1) revenues, employees, EBITDA, investments, cash flow, (stock, trend, cagr, expected trends) (2) share trends, market capitalization (3) geographical presence (4) current 1. TECHNOLOGY
market positioning and strategy (5) research
WORKBOOK
strategy
2. PLAYERS
Technologies
INFORMATION
Products/services: (1) service concept (2) biz model
S
(3) economics: users, revenues, margins, Cagr, 3. CONNECTION
ARPU
MATRIX
Environment
Relationships among actors - different kind of flows
through the ecosystem: exchanged information
Transactions
 connection matrix: per each couple of variable
it will be indicated: 0 - no relationship is on 1 if a link already exists and is intangible, 2 – if a
link already exists and is tangible, 3 – if a possible relation can be formed in a near future
ECOSYSTEM MODEL
REPRESENTATION
 Develop a representation model
Translate in a graphical way the connection matrix:
4. ECOSYSTEM
oriented graph; links and nodes characterized in a
REPRESENTAT
quantitative way; weight to each kind of relationION MODEL
ship
DATA VALIDATION
 Obtain criteria to validate the
 Brainstorming; existing literature; research con- 5. ECOSYSTEM
ducted by specialists from reference markets; offiREPRESENTATI
5
model
cial documents (budgets, communication to the financial community, business plans, etc.); direct
contact with the actors that belong to the potential
ecosystem; consulting experts in modeling complex
systems
ON MODEL
VALIDATED
ECOSYSTEM ANALYSIS
 Evaluation of the ecosystem’s
behaviours (last, current, future)
and relevant key indicators.
Ecosystem value analysis
 revenues: quantify the economic dimension of the
ecosystem
 economic structure: understand how this value is
shared among the various players: physical structure, revenues attraction, attractivity, relationship,
assets & technologies
6. ECOSYSTEM
Ecosystem control point analysis
ANALYSIS
 identification of control points (“points at which
management can be applied” - business strategy,
regulation, and/or technology); control points constellation: put control points in a logical sequence,
represent integrated control points as joined together; check for lock-in; show multiple offering outcomes if applicable
ECOSYSTEM EVOLUTION
 Simulation of different scenarios aimed to perform what-if
analysis, trend analysis, classification, forecasts.
 list of trends and uncertainties; early signs; scenari7. ECOSYSTEM
os graph; scenarios narrative; definition of possible
SCENARIOS
scenarios; list of implications and options of reANALYSIS
sponses
1. ECOSYSTEM PERIMETER, ELEMENTS AND RELATIONSHIPS The objective of this first step is to identify the perimeter and constituent parts of the ecosystem. In the digital imaging ecosystem, the seed is the service, based on the psychology of the “management of the memories” and the “digital translation” of the
reality, that permit new possibilities and functionalities for the personal sphere of
the individual. Another important point for the decision about the borders of the
object of observation are the constitutive elements of the ecosystem and the relationships among them. For the digital imaging ecosystem, the team preliminarily
identified two macro-classes of actors in the ecosystem and for each one listed the
component actors and the main players:
 Manufacturers: class of actors connected to the consumer-electronics production, in other words the hardware part of the ecosystem; they are typically
constrained to obtain cost-efficiency through scale-economies and realize
high production-volumes. They are: camera and camcorders manufacturers,
storage manufacturers, printers manufacturers, cameraphone manufacturers
 Service Providers: their offer is connected to services and not-tangible functionalities for users. They are: on line storage providers; photoalbum providers; social network providers; on-line printing providers; mobile applications
providers; software vendors providers; telco operators providers; retailers
providers
As regards the enabling technologies of the Digital Imaging Ecosystem, we
identified these categories: Computational photography, Sensors resolution and
6
quality, Still/motion convergence, Barcode / QR Code, RFID / NFC, GPS, Wireless / Mobile, Metadata Exif, 3D, Digital pictures and video playback.
The next step is the construction of the Connections Matrix which has the purpose to highlight the links between the constituent parts of the ecosystem. The
connection matrix of the Digital Imaging Ecosystem is in Table 3.
Fig. 1. Digital Imaging Ecosystem model representation [screenshot]
Fig. 2. Digital Imaging Ecosystem relationship structure
2-3. ECOSYSTEM MODEL REPRESENTATION and DATA VALIDATION
The objective of this step is to develop a representative model of the ecosystem.
For nodes, a color code is used to differentiate players who have a different role,
and a code volume to differentiate the weight of each actor. A parameter for the
weight factor could be the size (turnover, number of employees) where applicable.
For links, it is necessary to classify the different types of relationships with the criteria used in the connection matrix. See Figure 1.
7
Table 3. Digital Imaging Ecosystem connection matrix
MANUFACTURER
Printers manuf.
Cameraphone man
On line Storage
Photoalbum
Social Network
On line printing
Mobile apps
sw vendor (editing,applet,plug-in)
Telco operator
Sensors resolution and quality
Still/motion convergence
Barcode / QR Code
RFID/NFC
GPS
Wireless/Mobile
Metadata/EXIF
3D
Digital pictures and video playback
-
1
2
2
1
1
1
1
3
1
3
2
3
3
2
2
0
0
2
3
1
1
3
1
2
2
1
1
1
1
3
1
3
2
1
1
2
2
1
1
0
0
3
2
1
3
0
1
0
2
0
1
3
2
1
3
1
1
1
3
2
2
2
2
2
0
1
2
1
1
1
0
3
0
2
1
1
2
2
2
2
2
2
0
1
0
1
1
2
1
1
3
2
0
1
2
3
1
2
1
3
1
3
0
0
0
2
1
2
1
3
2
2
0
0
1
2
0
2
3
1
2
0
2
3
3
2
3
2
2
3
2
0
2
2
2
2
0
0
0
2
0
2
2
-
0
1
3
0
0
0
0
1
1
3
0
0
0
3
0
2
1
0
2
1
1
0
1
1
2
0
0
0
1
0
1
1
1
0
0
2
0
1
3
0
0
0
1
0
0
1
2
0
0
0
0
1
0
2
2
0
0
3
0
0
0
0
1
0
2
2
0
0
2
0
1
1
0
1
1
2
0
1
1
2
2
1
1
1
1
0
2
0
1
0
2
0
1
1
1
1
1
2
0
0
3
0
0
3
3
1
3
1
1
0
2
1
3
2
1
3
0
1
1
1
0
3
0
1
3
0
0
0
0
1
1
3
0
-
2
2
2
0
0
0
0
1
3
1
3
0
0
3
0
2
1
0
2
1
1
0
2
-
1
1
2
3
2
2
1
1
1
2
1
1
2
0
0
0
1
0
1
1
1
2
1
-
1
1
0
0
0
1
0
2
2
0
0
2
0
1
3
0
0
0
1
0
2
1
1
-
0
0
0
0
0
3
2
0
0
2
3
1
1
0
0
0
1
1
0
1
0
0
1
0
3
2
3
2
2
2
0
0
0
0
2
0
0
0
0
1
1
1
3
0
0
1
1
1
3
0
0
0
1
1
0
1
1
1
1
1
3
0
0
1
0
1
1
2
2
2
2
2
1
2
2
0
0
0
0
0
0
0
0
1
3
2
3
2
3
1
1
1
0
0
0
1
0
0
0
0
0
0
3
1
0
0
0
0
1
1
1
1
3
0
1
2
2
2
0
1
2
0
0
0
1
2
0
3
0
3
2
0
3
-
0
3
1
2
1
1
3
2
1
3
2
1
3
0
1
1
1
0
1
1
2
2
0
3
1
2
1
1
-
Retailers
Computational photography
player
Image recognition R&D player
Storage manuf.
R&D
TECHNOLOGY
Camera&camcorders manuf.
Camera&camcorders
manuf.
Storage manuf.
Printers manuf.
Cameraphone manuf.
On line Storage
Photoalbum
Social Network
On line printing
Mobile apps
Sw vendor
Telco operator
Retailers
Computational photography R&D player
Image
recognition
R&D player
Sensors resolution and
quality
Still/motion convergence
Barcode / QR Code
RFID/NFC
GPS
Wireless/Mobile
Metadata/EXIF
3D
Digital pictures and
video playback
SERVICE PROVIDER
4 ECOSYSTEM ANALYSIS The aim of this step is to analyze the behavior of
the ecosystem in the past and in the present. This involves understanding how the
value is distributed in each ecosystem and the best places to target the positioning
strategy to capture part of this available value. This requires two separate steps:
Business Ecosystem Value Analysis and Business Ecosystem Control Point Analysis. See figure 2. The control point analysis identified the pc and the smartphones
and mobile applications as control points of the digital imaging ecosystem. They
connect and control the ecosystem in two levels of connection: one between creation and storage/modification and one between storage/modification and services
(online printing and online storage).
8
5 ECOSYSTEM EVOLUTION In this step the possible evolutionary scenarios are
studied. For the digital imaging ecosystem we built a scenario analysis and a
roadmap for future evolution (Battistella and De Toni, 2011).
5. Conclusions
As businesses become more and more modularized, characterizing entity relationships and understanding how business decisions or actions taken by one entity impact all of the interrelated entities, both within and among enterprises, become a
key challenge. Ignoring these interactions can lead to unexpected and potentially
undesirable outcomes. Tools that help to systematically characterize the business
ecosystem (or network) and analyze the potential impact of different business decisions on each entity in the network are essential for improving business design.
The knowledge of a phenomenon is the basis of its evolution. The methodology
of business ecosystem network analysis (MOBENA) is a first step to build a tool
that can facilitate the knowledge about the business ecosystems, with a first improvement toward the standardization of the procedure for different contexts and
the reusability of data and information.
References
synthesises the five phases, giving a brief description of objectives, contents and
deliverables.
Table 2. MOBENA phases
PHASE and OBJECTIVES
ECOSYSTEM PERIMETER,
ELEMENTS AND
RELATIONSHIPS
 Define the meaning of the ecosystem, decide what identifies it
and identify what defines its
boundaries.
 Detail the information to be collected as regards the constitutive elements and their relationships.
CONTENT
DELIVERABLE
 Identify the seed – the actors’ attractor and the leverage for business.
 Identify the elements and their connections. Elements: players, technologies, products/services and
environment (market, constraints and regulation
forces)
Players: (1) revenues, employees, EBITDA, investments, cash flow, (stock, trend, cagr, ex- 8. TECHNOLOGY
pected trends) (2) share trends, market capitaliWORKBOOK
zation (3) geographical presence (4) current 9. PLAYERS
market positioning and strategy (5) research
INFORMATION
strategy
S
Technologies
10. CONNECTION
Products/services: (1) service concept (2) biz model
MATRIX
(3) economics: users, revenues, margins, Cagr,
ARPU
Environment
Relationships among actors - different kind of flows
through the ecosystem: exchanged information
Transactions
 connection matrix: per each couple of variable
9
ECOSYSTEM MODEL
REPRESENTATION
 Develop a representation model
it will be indicated: 0 - no relationship is on 1 if a link already exists and is intangible, 2 – if a
link already exists and is tangible, 3 – if a possible relation can be formed in a near future
Translate in a graphical way the connection matrix:
11. ECOSYSTEM
oriented graph; links and nodes characterized in a
REPRESENTAT
quantitative way; weight to each kind of relationION MODEL
ship
DATA VALIDATION
 Obtain criteria to validate the
model
 Brainstorming; existing literature; research conducted by specialists from reference markets; offi12. ECOSYSTEM
cial documents (budgets, communication to the fiREPRESENTATI
nancial community, business plans, etc.); direct
ON MODEL
contact with the actors that belong to the potential
VALIDATED
ecosystem; consulting experts in modeling complex
systems
ECOSYSTEM ANALYSIS
 Evaluation of the ecosystem’s
behaviours (last, current, future)
and relevant key indicators.
Ecosystem value analysis
 revenues: quantify the economic dimension of the
ecosystem
 economic structure: understand how this value is
shared among the various players: physical structure, revenues attraction, attractivity, relationship,
assets & technologies
13. ECOSYSTEM
Ecosystem control point analysis
ANALYSIS
 identification of control points (“points at which
management can be applied” - business strategy,
regulation, and/or technology); control points constellation: put control points in a logical sequence,
represent integrated control points as joined together; check for lock-in; show multiple offering outcomes if applicable
ECOSYSTEM EVOLUTION
 Simulation of different scenarios aimed to perform what-if
analysis, trend analysis, classification, forecasts.
 list of trends and uncertainties; early signs; scenari14. ECOSYSTEM
os graph; scenarios narrative; definition of possible
SCENARIOS
scenarios; list of implications and options of reANALYSIS
sponses
1. ECOSYSTEM PERIMETER, ELEMENTS AND RELATIONSHIPS The objective of this first step is to identify the perimeter and constituent parts of the ecosystem. In the digital imaging ecosystem, the seed is the service, based on the psychology of the “management of the memories” and the “digital translation” of the
reality, that permit new possibilities and functionalities for the personal sphere of
the individual. Another important point for the decision about the borders of the
object of observation are the constitutive elements of the ecosystem and the relationships among them. For the digital imaging ecosystem, the team preliminarily
identified two macro-classes of actors in the ecosystem and for each one listed the
component actors and the main players:
 Manufacturers: class of actors connected to the consumer-electronics production, in other words the hardware part of the ecosystem; they are typically
constrained to obtain cost-efficiency through scale-economies and realize
10
high production-volumes. They are: camera and camcorders manufacturers,
storage manufacturers, printers manufacturers, cameraphone manufacturers
 Service Providers: their offer is connected to services and not-tangible functionalities for users. They are: on line storage providers; photoalbum providers; social network providers; on-line printing providers; mobile applications
providers; software vendors providers; telco operators providers; retailers
providers
As regards the enabling technologies of the Digital Imaging Ecosystem, we
identified these categories: Computational photography, Sensors resolution and
quality, Still/motion convergence, Barcode / QR Code, RFID / NFC, GPS, Wireless / Mobile, Metadata Exif, 3D, Digital pictures and video playback.
The next step is the construction of the Connections Matrix which has the purpose to highlight the links between the constituent parts of the ecosystem. The
connection matrix of the Digital Imaging Ecosystem is in Table 3.
Fig. 1. Digital Imaging Ecosystem model representation [screenshot]
Fig. 2. Digital Imaging Ecosystem relationship structure
2-3. ECOSYSTEM MODEL REPRESENTATION and DATA VALIDATION
The objective of this step is to develop a representative model of the ecosystem.
For nodes, a color code is used to differentiate players who have a different role,
and a code volume to differentiate the weight of each actor. A parameter for the
weight factor could be the size (turnover, number of employees) where applicable.
11
For links, it is necessary to classify the different types of relationships with the criteria used in the connection matrix. See Figure 1.
Table 3. Digital Imaging Ecosystem connection matrix
MANUFACTURER
Printers manuf.
Cameraphone man
On line Storage
Photoalbum
Social Network
On line printing
Mobile apps
sw vendor (editing,applet,plug-in)
Telco operator
Sensors resolution and quality
Still/motion convergence
Barcode / QR Code
RFID/NFC
GPS
Wireless/Mobile
Metadata/EXIF
3D
Digital pictures and video playback
-
1
2
2
1
1
1
1
3
1
3
2
3
3
2
2
0
0
2
3
1
1
3
1
2
2
1
1
1
1
3
1
3
2
1
1
2
2
1
1
0
0
3
2
1
3
0
1
0
2
0
1
3
2
1
3
1
1
1
3
2
2
2
2
2
0
1
2
1
1
1
0
3
0
2
1
1
2
2
2
2
2
2
0
1
0
1
1
2
1
1
3
2
0
1
2
3
1
2
1
3
1
3
0
0
0
2
1
2
1
3
2
2
0
0
1
2
0
2
3
1
2
0
2
3
3
2
3
2
2
3
2
0
2
2
2
2
0
0
0
2
0
2
2
-
0
1
3
0
0
0
0
1
1
3
0
0
0
3
0
2
1
0
2
1
1
0
1
1
2
0
0
0
1
0
1
1
1
0
0
2
0
1
3
0
0
0
1
0
0
1
2
0
0
0
0
1
0
2
2
0
0
3
0
0
0
0
1
0
2
2
0
0
2
0
1
1
0
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1
2
0
1
1
2
2
1
1
1
1
0
2
0
1
0
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1
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1
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1
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Retailers
Computational photography
player
Image recognition R&D player
Storage manuf.
R&D
TECHNOLOGY
Camera&camcorders manuf.
Camera&camcorders
manuf.
Storage manuf.
Printers manuf.
Cameraphone manuf.
On line Storage
Photoalbum
Social Network
On line printing
Mobile apps
Sw vendor
Telco operator
Retailers
Computational photography R&D player
Image
recognition
R&D player
Sensors resolution and
quality
Still/motion convergence
Barcode / QR Code
RFID/NFC
GPS
Wireless/Mobile
Metadata/EXIF
3D
Digital pictures and
video playback
SERVICE PROVIDER
4 ECOSYSTEM ANALYSIS The aim of this step is to analyze the behavior of
the ecosystem in the past and in the present. This involves understanding how the
value is distributed in each ecosystem and the best places to target the positioning
strategy to capture part of this available value. This requires two separate steps:
Business Ecosystem Value Analysis and Business Ecosystem Control Point Analysis. See figure 2. The control point analysis identified the pc and the smartphones
12
and mobile applications as control points of the digital imaging ecosystem. They
connect and control the ecosystem in two levels of connection: one between creation and storage/modification and one between storage/modification and services
(online printing and online storage).
5 ECOSYSTEM EVOLUTION In this step the possible evolutionary scenarios are
studied. For the digital imaging ecosystem we built a scenario analysis and a
roadmap for future evolution (Battistella and De Toni, 2011).
5. Conclusions
As businesses become more and more modularized, characterizing entity relationships and understanding how business decisions or actions taken by one entity impact all of the interrelated entities, both within and among enterprises, become a
key challenge. Ignoring these interactions can lead to unexpected and potentially
undesirable outcomes. Tools that help to systematically characterize the business
ecosystem (or network) and analyze the potential impact of different business decisions on each entity in the network are essential for improving business design.
The knowledge of a phenomenon is the basis of its evolution. The methodology
of business ecosystem network analysis (MOBENA) is a first step to build a tool
that can facilitate the knowledge about the business ecosystems, with a first improvement toward the standardization of the procedure for different contexts and
the reusability of data and information.
References
Examples of Digital Imaging ecosystem are taken from an other workgroup in Telecom Italia Future
Centre led by G. Piersantelli, http://www.telecomfuturecentre.it/ecosistemi/foto_digitale.shtml
1.
Allee, V. (2002) The Future of Knowledge: Increasing Prosperity through Value Networks, Boston: ButterworthHeinemann.
2. Battistella, C. and De Toni A.F. (2011) A methodology of technological foresight: A proposal
3. and field study, Technology forecasting and social change, 78 (6): 1029–1048.
4. De Toni, A.F. and F. Nonino (2010), The key roles in the informal organization: a network 194
5. perspective analysis, The learning organization, 10(1):86–103.
6. Durlauf, S.N. and Fafchamps, M. (2004) Social Capital. NBER,Working Paper # W10485, 2004.
Available at SSRN: http://ssrn.com/abstract=546282
7. Gordijn, J., Akkermans J.M. and Vliet J.C. Van, (2000) Business Modeling is not Process Modeling, In Conceptual Modeling for E-Business and the Web, Springer-Verlag, 40-51
8. Iansity, M., Levien, R. (2004) Keystones and Dominators: Framing Operating and Technology
Strategy in a Business Ecosystem, Harvard Business School, Working Paper #03-061.
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Natural Ecosystems and Multi-Agent Systems. Lecture Notes in Computer Science. 4676.
10. Porter, Michael E., 'Competitive advantage: creating and sustaining superior performance', Free
Press, New York, 1985
11. Tian, C.H., et al. (2008) BEAM: a framework for business ecosystem analysis and modeling.
IBM Systms Journal, 47(1): 101-114
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(2007) Strategic Analysis using Value Modelling – a c3 approach, In Prooceedings of the 40th
Hawaii InternationaI Conference on System Sciences.